So sánh phương pháp
Xem các phương pháp đã chọn cạnh nhau; những hàng khác biệt được làm nổi bật.
| M/M/c Queue: Mô hình Hàng đợi Đa máy chủ× | Định luật Little (L = λW)× | |
|---|---|---|
| Lĩnh vực | Vận trù học | Vận trù học |
| Họ | Regression model | Regression model |
| Năm ra đời≠ | 1998 | 1961 |
| Người khởi xướng≠ | Queueing-theory tradition; Gross & Harris | John D. C. Little |
| Loại≠ | Multi-server Markovian queueing model | Exact queueing identity |
| Công trình gốc≠ | Gross, D., & Harris, C. M. (1998). Fundamentals of Queueing Theory (3rd ed.). Wiley. ISBN: 978-0-471-17083-9 | Little, J. D. C. (1961). A proof for the queuing formula: L = λW. Operations Research, 9(3), 383–387. DOI ↗ |
| Tên gọi khác | Multi-Server Erlang Queue, c-Server Markovian Queue, Erlang-C Queue, Çok Sunuculu M/M/c Kuyruğu | L = λW Theorem, Little's Theorem, Little's Result, Little Yasası |
| Liên quan | 3 | 3 |
| Tóm tắt≠ | The M/M/c queue is a multi-server stochastic model in which customers arrive according to a Poisson process at rate λ, are served by c identical servers each with exponentially distributed service times at rate μ, and wait in a single common queue when all servers are busy. Systematized within classical queueing theory and thoroughly treated by Gross and Harris (1998), it extends the simpler M/M/1 model to settings with parallel servers, making it the foundational tool for capacity planning in service systems. | Little's Law is a fundamental theorem in queueing theory that relates the long-run average number of items in a stable system (L) to the long-run average arrival rate (λ) and the long-run average time an item spends in the system (W), expressed as L = λW. Introduced and rigorously proved by John D. C. Little in 1961, the law holds for virtually any stable stochastic system, requiring no assumptions about arrival distributions, service distributions, or queue disciplines. |
| ScholarGateBộ dữ liệu ↗ |
|
|